From Tools to Teammates: Navigating the New Human-AI Relationship
Source: Upwork Research Institute with Workplace Intelligence · 2025-07-09
The study, From Tools to Teammates: Navigating the New Human-AI Relationship, is the latest installment in a multi-year research series examining the evolving relationship between AI, productivity, and the workforce. Building on last year’s findings—where 77% of employees reported AI had increased their workload—this year’s report finds many workers are now reporting a 40% boost in productivity with AI, but at a significant emotional and relational cost.
Based on a global survey of 2,500 workers, including C-suite executives, full-time employees, and independent freelancers, the new research offers a timely look at how AI is reshaping not just how work gets done, but how individuals relate to their tools, teams, and organizations. The findings come as AI and AI agents are becoming increasingly embedded in workflows. Monthly searches for Upwork talent skilled in AI agents have grown nearly 300% over the past six months, as of May 2025.
“AI is no longer just a background tool—it’s becoming a central part of how we work and interact,” said Dr. Kelly Monahan, managing director of the Upwork Research Institute. “It’s unlocking speed and scale, but also reshaping how we collaborate and connect as humans. The productivity paradox we’re seeing may be a natural growing pain of traditional work systems, ones that reward output with AI, but overlook the human relationships behind that work. To lead effectively in the age of AI, companies need to redesign work in ways that support not just efficiency, but also well-being, trust, and long-term resilience.”
Productivity gains are accelerating: Employees using AI report a 40% boost in productivity on average. This improvement is fueled by increased comfort with the tools because they’ve had time to experiment (according to 30% of respondents), continued product enhancements of tools (25%), self-directed upskilling (22%), and employer-supported training (22%). Organizations are seeing the payoff, as 77% of C-suite leaders say they’ve observed productivity gains from AI adoption across their teams in the past year.
But productivity comes at a cost: Workers who report the highest productivity gains due to AI are also the most burned out: 88% say they are experiencing burnout, and they are twice as likely to consider quitting, compared to workers who are less productive with AI tools. Many of these top performers also feel disconnected from their organization’s broader AI strategy, as 62% say they don’t understand how their daily use of AI aligns with company goals. This disconnect highlights an emerging risk: Without clear alignment and support, even the most proficient AI users become flight risks.
Workplace trust and connection are shifting: More than two-thirds of high-performing AI users say they trust AI more than their coworkers, and 64% say they have a better relationship with AI than with human colleagues. The majority of high-performing AI users say AI is more polite and empathetic than their teammates, prompting a reevaluation of what “teamwork” looks like.
The rise of AI-human dynamics: Nearly half of all workers say “please” and “thank you” with every single request submitted to AI, and 87% phrase requests as if to a human coworker at least some of the time. This trend toward anthropomorphizing AI reveals the emotional depth of the human-AI relationship and signals that organizations may need to rethink how they design communication norms, workflows, and team dynamics.
Freelancers model healthier relationships with AI: Unlike many full-time employees, freelancers appear to thrive alongside AI. Nearly nine in 10 freelancers say AI has a positive impact on their work, and 42% credit it with helping them specialize in a particular niche. These workers are using AI primarily as a learning partner, with 90% saying it helps them acquire new skills faster. Freelancers are also more likely than FTEs to see a direct link between AI use, skill development, and tangible career outcomes like productivity gains and business growth.
“We’re observing a major inflection point in how work gets done,” said Dr. Gabby Burlacu, senior research manager of the Upwork Research Institute. “Over three-quarters of C-suite leaders and employees believe AI agents will completely reinvent the way people work. The real opportunity isn’t just deploying AI; it’s designing the organizational systems where humans and AI can thrive together.”
The path to sustainable, AI-empowered organizations requires reimagining work as a collaboration between humans and AI, cultivating flexible and resilient talent ecosystems, and redefining AI strategies around relationships, emerging AI roles, and responsible governance.
Research findings are based on a survey conducted by Walr, on behalf of Upwork and Workplace Intelligence, between March 25 and April 9, 2025. The survey targeted respondents in the U.S., U.K., Australia, and Canada. In total, 2,500 global workers completed the survey, including 1,250 C-suite executives, 625 full-time, salaried employees, and 625 freelancers. The survey sampled a mix of male and female respondents, as well as a mix of respondents from different generations (Gen Z, Millennials, Gen X, and Baby Boomers). All respondents were between the ages of 18 and 78, were required to have at least a high school diploma, and were required to use a laptop or computer for their work at least “sometimes.” Employees in the top quartile for self-reported AI-related productivity gains were compared to their peers along dimensions of burnout, intentions to quit, and preference for AI tools vs. human colleagues.
Lines of inquiry this paper opens 24
Research framings built by reading the notes related to this paper — the questions it feeds into.
Can we reliably measure and demonstrate AI's actual productivity impact?- Does lack of strategic alignment between AI use and company goals drive burnout?
- Will AI gains raise wages for all workers or widen inequality?
- Are entry-level workers bearing the labor costs of AI productivity gains?
- What parts of professional tasks do workers find intrinsically motivating?
- Can worker time savings exist without visible productivity gains?
- Can productivity gains for low-skill workers reduce income inequality?
- How do capital and labor shares respond to AI productivity gains?
- Can humans using superhuman AI actually increase their own novel problem-solving?
- When does task reorganization from AI actually translate into wage changes?
- Do workers who hide AI use experience different anxiety about job displacement?
- Do scope gains from AI create job instability despite higher output?
- Why do early-career workers fear AI job loss more than senior workers?
- Why does removing routine clerical tasks increase demand for skilled technical roles?
- Do workers experience AI-driven work changes differently moment-to-moment versus in retrospect?
- Does AI job-loss fear match actual hiring or employment declines?
- How do young workers in AI-exposed jobs respond to adoption differently?
- What specific manager behaviors reduce worker anxiety about AI displacement?
- Can worker engagement and burnout be tied to displacement concern alone?
- Do most people actually derive their primary meaning from employment?
- What happens to wage structures as AI accelerates labor displacement?
- Why do aggregate employment statistics miss losses in specific occupations?
- What happened to workers after previous technological shifts like free trade?
- How much do frontline workers actually experience these three problems?
- Which AI technologies actually create new jobs versus replace workers?